Simulation Based Tropospheric Error Estimation Performance Analysis with Low Earth Orbit (LEO) Satellites

PPP is a satellite-based precise absolute positioning technique, in which the user receives corrections about satellite orbit, time, and hardware bias from an external augmentation system. The user determines the precise satellite orbit of their visible satellite based on the provided correction information, and after removing the ionospheric error using the iono-free linear combination, the remaining troposphere error in the signal is estimated together with the ambiguity included in the carrier measurements. At this process, the Kalman filter is utilized, and since the number of estimated states is greater than that of other positioning techniques, the initial convergence time of PPP is generally known to be more than 20 minutes. Among the estimated errors, tropospheric errors are usually divided into hydrostatic delay and wet delay. Hydrostatic delay can be eliminated almost completely because the existing model fits well. However, it is known that it is impossible to eliminate all wet delay errors because the accuracy of the wet delay model is not as high as that of the dry delay model. Tropospheric delay is modeled as the vertical delay in the zenith direction multiplied by a mapping function, but since the variation of the line-of-sight vector of each satellite is not large, it is difficult to estimate it quickly and accurately using a Kalman filter. Recently, with the advent of the new space era, research on PNT (Positioning, Navigation and Timing) techniques using various LEO (Low Earth Orbit) satellites is being actively conducted. Since the LEO satellite-based PNT has very different dynamic characteristics from the existing MEO (Middle Earth Orbit satellites), it shows different error characteristics from the MEO-based GNSS. In particular, since the troposphere error is greatly related to the user's line of sight vector, if PPP is performed using a LEO satellite whose line of sight vector changes rapidly, it can be expected to show faster and more accurate troposphere error estimation performance. Therefore, in this study, the troposphere wet delay error estimation performance based on a LEO satellite was verified based on a simulation. In addition, the PPP performance of LEO PNT, which will be launched in the future, was analyzed by applying the scale-down technique to actual observation data.